Anthony J Deo, Victor M Castro, Ashley Baker, Devon Carroll, Joseph Gonzalez-Heydrich, David C Henderson, Daphne J Holt, Kimberly Hook, Rakesh Karmacharya, Joshua L Roffman, Emily M Madsen, Eugene Song, William G Adams, Luisa Camacho, Sarah Gasman, Jada S Gibbs, Rebecca G Fortgang, Chris J Kennedy, Galina Lozinski, Daisy C Perez, Marina Wilson, Ben Y Reis, Jordan W Smoller
{"title":"在三个医疗系统中验证基于 ICD 代码的精神病病例定义。","authors":"Anthony J Deo, Victor M Castro, Ashley Baker, Devon Carroll, Joseph Gonzalez-Heydrich, David C Henderson, Daphne J Holt, Kimberly Hook, Rakesh Karmacharya, Joshua L Roffman, Emily M Madsen, Eugene Song, William G Adams, Luisa Camacho, Sarah Gasman, Jada S Gibbs, Rebecca G Fortgang, Chris J Kennedy, Galina Lozinski, Daisy C Perez, Marina Wilson, Ben Y Reis, Jordan W Smoller","doi":"10.1093/schbul/sbae064","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and hypothesis: </strong>Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.</p><p><strong>Study design: </strong>Using EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings.</p><p><strong>Study results: </strong>PPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62).</p><p><strong>Conclusions: </strong>We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.</p>","PeriodicalId":21530,"journal":{"name":"Schizophrenia Bulletin","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11548932/pdf/","citationCount":"0","resultStr":"{\"title\":\"Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems.\",\"authors\":\"Anthony J Deo, Victor M Castro, Ashley Baker, Devon Carroll, Joseph Gonzalez-Heydrich, David C Henderson, Daphne J Holt, Kimberly Hook, Rakesh Karmacharya, Joshua L Roffman, Emily M Madsen, Eugene Song, William G Adams, Luisa Camacho, Sarah Gasman, Jada S Gibbs, Rebecca G Fortgang, Chris J Kennedy, Galina Lozinski, Daisy C Perez, Marina Wilson, Ben Y Reis, Jordan W Smoller\",\"doi\":\"10.1093/schbul/sbae064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and hypothesis: </strong>Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.</p><p><strong>Study design: </strong>Using EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings.</p><p><strong>Study results: </strong>PPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62).</p><p><strong>Conclusions: </strong>We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.</p>\",\"PeriodicalId\":21530,\"journal\":{\"name\":\"Schizophrenia Bulletin\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11548932/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Schizophrenia Bulletin\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/schbul/sbae064\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Schizophrenia Bulletin","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/schbul/sbae064","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems.
Background and hypothesis: Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.
Study design: Using EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings.
Study results: PPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62).
Conclusions: We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.
期刊介绍:
Schizophrenia Bulletin seeks to review recent developments and empirically based hypotheses regarding the etiology and treatment of schizophrenia. We view the field as broad and deep, and will publish new knowledge ranging from the molecular basis to social and cultural factors. We will give new emphasis to translational reports which simultaneously highlight basic neurobiological mechanisms and clinical manifestations. Some of the Bulletin content is invited as special features or manuscripts organized as a theme by special guest editors. Most pages of the Bulletin are devoted to unsolicited manuscripts of high quality that report original data or where we can provide a special venue for a major study or workshop report. Supplement issues are sometimes provided for manuscripts reporting from a recent conference.